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Screens: some commentsUniv.Prof.dr. Maarten C.W. Janssen
CEG Europe
General Principles
Statistical inferenceDo conflicting hypotheses yields sufficiently different predictions that
on the basis of empirical evidence we can discriminate between
them?
Quality of Data
Cost-benefit analysis whether or not to engage in it Compare cost/benefits alternatives (e.g., leniency program for cartel
detection purposes)
How difficult is it to get data? how likely you get conclusive results?
Sometimes almost no alternative available, e.g., when calculating
damages
How well can we distinguish between collusion and competition?All firms charge same price
Could also be the outcome of Bertrand competition with identical cost
But if firms have different cost …For this we need to have cost data
Cost pass through (how much of cost changes is passed through in terms of prices)
No information on cost per se needed, only cost changes
Cost pass through smaller than 1 sign of market power, collusion
But monopolist with two part tariff also has a cost pass through of 1 in the price per unit
Mobile telephony in Netherlands: retail price per minute does not react (or negatively to termination rates)
Everyone believes this is a competitive market
An example from own research (joint with Riemer Faber)In NL large gasoline companies (Shell, BP, Esso, etc.) daily announce a suggested price to (their) retailers Do these suggested prices help retailers coordinate prices?
Our hypotheses: With suggested prices, price difference between any two pair of retailers much more stable than without them
Retailers advertise “I am x cents below suggested price”
We looked at so-called rank reversal test
For any pair of stations, we look at how often (% of days) the
station that is most often more expensive, is actually cheaper
First we consider Vienna
Wien, Euro 95
Amsterdam, Euro 95
0
200
400
600
800
1000
1200
1400
0.0 0.1 0.2 0.3 0.4
Series: REVERSAL2Sample 1 3782Observations 1865
Mean 0.057176Median 0.004193Maximum 0.469388Minimum 0.000000Std. Dev. 0.097575Skewness 1.986917Kurtosis 6.301016
Jarque-Bera 2073.884Probability 0.000000
Rotterdam, Euro 95
0
400
800
1200
1600
0.0 0.1 0.2 0.3 0.4
Series: REVERSAL2Sample 1 4830Observations 2393
Mean 0.057102Median 0.003623Maximum 0.457143Minimum 0.000000Std. Dev. 0.092841Skewness 1.895103Kurtosis 6.058314
Jarque-Bera 2364.977Probability 0.000000
What to conclude?Is this enough evidence to have some conjecture that “something is going on”? How to investigate this further?
Or, are there other explanations? Maybe Dutch market is more oriented towards the international spot market and suggested prices translate spot market price into retail price?
We did advanced econometric model where we studied whether suggested price contains more information than spot market price to predict retail prices
Answer is: yes, quite a bit?
Maybe retailer’s input price is linked to suggested price and retailers simply react to their cost price?
Don’t have independent evidence on cost prices.
Concluding
Screens can be extremely useful
But have to be applied with great care
Often issues are not as simple as they seem at first sight if one
wants to eliminate alternative explanations
Often: no conclusive proof
good for detection purposes
But only if data are relatively easily available and it is clear what
are different testable implications of alternative hypotheses
Sometimes few alternatives available (like when used to calculate damages)